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  2. Circular error probable - Wikipedia

    en.wikipedia.org/wiki/Circular_error_probable

    There are associated concepts, such as the DRMS (distance root mean square), which is the square root of the average squared distance error, a form of the standard deviation. Another is the R95, which is the radius of the circle where 95% of the values would fall, a 95% confidence interval .

  3. Circular distribution - Wikipedia

    en.wikipedia.org/wiki/Circular_distribution

    In probability and statistics, a circular distribution or polar distribution is a probability distribution of a random variable whose values are angles, usually taken to be in the range [0, 2π). [1] A circular distribution is often a continuous probability distribution , and hence has a probability density , but such distributions can also be ...

  4. Probability of error - Wikipedia

    en.wikipedia.org/wiki/Probability_of_error

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  5. von Mises distribution - Wikipedia

    en.wikipedia.org/wiki/Von_Mises_distribution

    In probability theory and directional statistics, the von Mises distribution (also known as the circular normal distribution or the Tikhonov distribution) is a continuous probability distribution on the circle. It is a close approximation to the wrapped normal distribution, which is the circular analogue of the normal distribution.

  6. Circular Error Probability - Wikipedia

    en.wikipedia.org/?title=Circular_Error...

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  7. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables ⁡ (+) = ⁡ + ⁡ + ⁡ (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...

  8. Convergence of random variables - Wikipedia

    en.wikipedia.org/wiki/Convergence_of_random...

    When X n converges in r-th mean to X for r = 1, we say that X n converges in mean to X. When X n converges in r-th mean to X for r = 2, we say that X n converges in mean square (or in quadratic mean) to X. Convergence in the r-th mean, for r ≥ 1, implies convergence in probability (by Markov's inequality).

  9. Probable error - Wikipedia

    en.wikipedia.org/wiki/Probable_error

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